Staff Software Engineer - Google Workspace, AI/ML

• Work on next generation batch processing infrastructure for Gmail in powering new user experiences.
• Work on Workspace wide convergence projects to bolster security and trust posture across the board.
• Work on processing and security technologies to shape the secure data consumption for Gmail and overall workspace.
• Identify and solve full stack issues with in-depth collaboration with core infrastructure teams towards next-generation batch processing and data validation initiatives.
• Define best practices to measure, monitor and improve data security, compliance for Gmail and chat to meet our trust and compliance requirements.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading Machine Learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience testing, and launching software products.
• 3 years of experience with software design and architecture.

Preferred qualifications:

• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in an organization involving cross-functional, or cross-business projects.

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Gmail Trust and Compliance Infrastructure's mission is to build and maintain infrastructure to keep Gmail and Chat data secure, and to enable rapid development of GenAI based features in Gmail, Workspace and across Google.

The team builds services and pipelines that ensure safety, compliance and the processing of all of Gmail data at scale. Gmail is one of the largest consumer products in the world. This large scale brings unique issues for any technology we use. The team builds and maintains batch and incremental processing infrastructure that can reliably process all of Gmail data within tight Service Level Objectives (SLOs), to power key features for our customers.

AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Mountain View, CA, USA.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading Machine Learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience testing, and launching software products.
• 3 years of experience with software design and architecture.